DOI: 10.5176/2251-2039_IE16.32
Authors: Damitha Bandara and Lakmali Weerasena
Abstract: Researchers are interested in developing efficient algorithms to solve combinatorial optimization problems (COPs) in reasonable execution time. Metaheuristic algorithms have showed their usefulness of solving COPs promptly when traditional solution methods get stuck while finding the optimal solution [1]. The objective of this research is to compare the performance of two widely used Metaheurstic algorithms to identify the best algorithm, when obtaining the solutions for COPs. Two types of Metaheuristics: the Genetic Algorithm (GA) and the Variable Neighborhood Search (VNS) method are used in the comparison. A real-life application of the set covering problem which is one of the well-known COPs is used as the test COP. The results show that the GA has a better solution quality while the VNS has a faster execution time for this application problem.
Keywords: component; : Metaheuristics, Genetic Algorithm, Variable Neighborhood Search, Combinatorial Optimization, Set Covering Problem
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